1. Field of the Invention
The present invention relates to periodic signal detection in a system, and more particularly, to periodic signal detection in an OFDM/DMT system.
2. Description of the Prior Art
Signal detection and receiver training are essential tasks for a digital communication system. Without accurate receiver training algorithms, it is not possible to reliably receive the transmitted data. In orthogonal frequency division multiplexing (OFDM) and discrete multi-tone (DMT) communication systems, data is modulated on tones used by the system. Inverse FFT (IFFT) is performed on the modulated tones to obtain a set of time domain samples called OFDM symbol for transmission. DMT is mainly used in continuous transmission systems, such as ADSL and VDSL; while OFDM is used in both continuous and burst transmission systems, such as European digital video broadcast (DVB), 802.11 wireless LANs, and 802.16 fixed wireless systems. OFDM/DMT communication systems use a periodic signal to facilitate signal detection, timing/frequency recovery, and channel estimation at the receiver. A periodic signal contains repeated training symbols, which are designed to possess good time domain and/or frequency domain auto-correlation property. The task of periodic signal detection is to detect arrival of data packets or the beginning of a periodic training signal with high probability of detection and low probability of false alarms under severe frequency selective channel fading and strong interferences.
Most of the existing periodic signal detection methods exploit repeated structures and auto-correlation property of periodic signaling time domain. These methods suffer significant performance degradation when strong narrowband interference (NBI) or Gaussian noise is present. In one approach known in the art, the time domain correlator computes auto-correlation values using current received temporal symbol and previous received temporal symbol until the correlation value exceeds a pre-defined threshold. This method, however, requires a large number of multiplication and addition operations. Time domain correlation is also difficult to establish if the received signal is corrupted by narrowband interference.
Frequency domain methods that correlate tone phases or other information of two consecutive received OFDM symbols achieve excellent periodic signal detection even in the presence of strong narrowband interference. For example, in another approach known in the art, two consecutive received temporal symbols are transformed into frequency domain by FFT operation. Two sets of tone phases are computed for the two frequency domain symbols. Correlation of the two sets of tone phases are computed as a metric for periodic signal detection. The computation requires heavy CPU cycles or complex ASIC implementation that amounts to higher system cost. Also, computation of tone phases adds overhead for communication systems that do not use phase information explicitly.